Department
Barowsky School of Business
Document Type
Article
Source
Computer Sciences and Mathematics Forum
Publication Date
2023
Volume
8
Issue
1
First Page
70
Abstract
Recent advances in large language models, our understanding of the general theory of information, and the availability of new approaches to building self-regulating domain-specific software are driving the creation of next-generation knowledge-driven digital assistants to improve the efficiency, resiliency, and scalability of various business processes while fulfilling the functional requirements addressing a specific business problem. Here, we describe the implementation of a medical-knowledge-based digital assistant that uses medical knowledge derived from various sources including the large language models and assists the early medical diagnosis process by reducing the knowledge gap between the patient and medical professionals involved in the process.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Comments
Presented at the Workshop on AI and People, IS4SI Summit 2023, Beijing, China, 14–16 August 2023